Network approach reveals the spatiotemporal influence of traffic on air pollution under COVID-19

空气污染 空气质量指数 北京 污染 环境科学 中国 气象学 环境工程 地理 生态学 生物 考古 有机化学 化学
作者
Weiping Wang,Saini Yang,Kai Yin,Zhi-Dan Zhao,Na Ying,Shlomo Havlin
出处
期刊:Chaos [American Institute of Physics]
卷期号:32 (4) 被引量:7
标识
DOI:10.1063/5.0087844
摘要

Air pollution causes widespread environmental and health problems and severely hinders the quality of life of urban residents. Traffic is critical for human life, but its emissions are a major source of pollution, aggravating urban air pollution. However, the complex interaction between traffic emissions and air pollution in cities and regions has not yet been revealed. In particular, the spread of COVID-19 has led various cities and regions to implement different traffic restriction policies according to the local epidemic situation, which provides the possibility to explore the relationship between urban traffic and air pollution. Here, we explore the influence of traffic on air pollution by reconstructing a multi-layer complex network base on the traffic index and air quality index. We uncover that air quality in the Beijing–Tianjin–Hebei (BTH), Chengdu–Chongqing Economic Circle (CCS), and Central China (CC) regions is significantly influenced by the surrounding traffic conditions after the outbreak. Under different stages of the fight against the epidemic, the influence of traffic in some regions on air pollution reaches the maximum in stage 2 (also called Initial Progress in Containing the Virus). For the BTH and CC regions, the impact of traffic on air quality becomes bigger in the first two stages and then decreases, while for CC, a significant impact occurs in phase 3 among the other regions. For other regions in the country, however, the changes are not evident. Our presented network-based framework provides a new perspective in the field of transportation and environment and may be helpful in guiding the government to formulate air pollution mitigation and traffic restriction policies.
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